Friday 17 January 2014

IEEE Transactions on Neural Networks and Learning Systems, Volume 25, Issue 2, February 2014

1. What Are the Differences Between Bayesian Classifiers and Mutual-Information Classifiers?
Author(s): Bao-Gang Hu
Pages: 249 - 264

2. Multikernel Least Mean Square Algorithm
Author(s): Felipe A. Tobar; Sun-Yuan Kung; Danilo P. Mandic
Pages: 265 - 277

3. Quantum Neural Network-Based EEG Filtering for a Brain-Computer Interface
Author(s): Vaibhav Gandhi; Girijesh Prasad; Damien Coyle; Laxmidhar Behera; Thomas Martin McGinnity
Pages: 278 - 288

4. Multiclass From Binary: Expanding One-Versus-All, One-Versus-One and ECOC-Based Approaches
Author(s): Anderson Rocha; Siome Klein Goldenstein
Pages: 289 - 302

5. Short-Term Load and Wind Power Forecasting Using Neural Network-Based Prediction Intervals
Author(s): Hao Quan; Dipti Srinivasan; Abbas Khosravi
Pages: 303 - 315

6. HRLSim: A High Performance Spiking Neural Network Simulator for GPGPU Clusters
Author(s): Kirill Minkovich; Corey M. Thibeault; Michael John O’Brien; Aleksey Nogin; Youngkwan Cho; Narayan Srinivasa
Pages: 316 - 331

7. Sliding-Mode Control Design for Nonlinear Systems Using Probability Density Function Shaping
Author(s): Yu Liu; Hong Wang; Chaohuan Hou
Pages: 332 - 343

8. Nanophotonic Reservoir Computing With Photonic Crystal Cavities to Generate Periodic Patterns
Author(s): Martin Andre Agnes Fiers; Thomas Van Vaerenbergh; Francis Wyffels; David Verstraeten; Benjamin Schrauwen; Joni Dambre; Peter Bienstman
Pages: 344 - 355

9. Efficient Probabilistic Classification Vector Machine With Incremental Basis Function Selection
Author(s): Huanhuan Chen; Peter Tino; Xin Yao
Pages: 356 - 369

10. Zhang Neural Network for Online Solution of Time-Varying Linear Matrix Inequality Aided With an Equality Conversion
Author(s): Dongsheng Guo; Yunong Zhang
Pages: 370 - 382

11. Robust Pole Assignment for Synthesizing Feedback Control Systems Using Recurrent Neural Networks
Author(s): Xinyi Le; Jun Wang
Pages: 383 - 393

12. Efficient Dual Approach to Distance Metric Learning
Author(s): Chunhua Shen; Junae Kim; Fayao Liu; Lei Wang; Anton van den Hengel
Pages: 394 - 406

13. Event-Based Visual Flow
Author(s): Ryad Benosman; Charles Clercq; Xavier Lagorce; Sio-Hoi Ieng; Chiara Bartolozzi
Pages: 407 - 417

14. Decentralized Stabilization for a Class of Continuous-Time Nonlinear Interconnected Systems Using Online Learning Optimal Control Approach
Author(s): Derong Liu; Ding Wang; Hongliang Li
Pages: 418 - 428

15. Novel Adaptive Strategies for Synchronization of Linearly Coupled Neural Networks With Reaction-Diffusion Terms
Author(s): Jin-Liang Wang; Huai-Ning Wu; Lei Guo
Pages: 429 - 440

Thursday 16 January 2014

IEEE Transactions on Computational Intelligence and AI in Games, Volume 5, Number 4, December 2013

1. A Survey of Real-Time Strategy Game AI Research and Competition in StarCraft
Author(s): Ontanon, S. ; Synnaeve, G. ; Uriarte, A. ; Richoux, F. ; Churchill, D. ; Preuss, M.
Pages: 293-311

2. Repeated Goofspiel: A Game of Pure Strategy
Author(s): Dror, M. ; Kendall, G.
Pages: 312-324

3. A Heuristic-Based Planner and Improved Controller for a Two-Layered Approach for the Game of Billiards
Author(s): Landry, J.-F. ; Dussault, J.-P. ; Mahey, P.
Pages: 325-336

4. Automated 3-D Animation From Snooker Videos With Information-Theoretical Optimization
Author(s): Jiang, R. ; Parry, M.L. ; Legg, P.A. ; Chung, D.H.S. ; Griffiths, I.W.
Pages: 337-345

5. Incentive Learning in Monte Carlo Tree Search
Author(s): Kao, K.-Y. ; Wu, I-C. ; Yen, S.-J. ; Shan, Y.-C.
Pages: 346-352

Tuesday 14 January 2014

Call for papers: Special session for WCCI 2014 "Evolutionary Computation for Music, Art, and Creativity"

Aim and Scope

Evolutionary computation (EC) techniques, including genetic algorithm, evolution strategies, genetic programming, particle swarm optimization, ant colony optimization, differential evolution, and memetic algorithms, have shown to be effective for search and optimization problems. Recently, EC gained several promising results and becomes an important tool in computational creativity, such as in music, visual art, literature, architecture, and industrial design.

The aim of this special session is to reflect the most recent advances of EC for Music, Art, and Creativity, with the goal to enhance autonomous creative systems as well as human creativity. This session will allow researchers to share experiences and present their new ways for taking advantage of EC techniques in computational creativity. Topics of interest include, but are not limited to, EC technologies in the following aspects:
  • Generation of music, visual art, literature, architecture, and industrial design
  • Algorithmic design in creative intelligence
  • Optimization in creativity
  • Development of hardware and software for creative systems
  • Evaluation methodologies
  • Assistance of human creativity
  • Computational aesthetics
  • Emotion response
  • Human-machine creativity

Deadline

The deadline for submissions to this special session is 20 January 2014.

Information for Authors

1. Information on the format and templates for papers can be found here: 
    http://www.ieee-wcci2014.org/Paper%20Submission.htm
2. Papers should be submitted via the IEEE CEC 2014 paper submission site:   
    http://ieee-cis.org/conferences/cec2014/upload.php
3. Select the Special Session name in the Main Research topic dropdown list:   
    [SS3. EC03: Evolutionary Computation for Music, Art, and Creativity]
4.    Fill out the input fields, upload the PDF file of your paper and finalize your submission by the deadline of January 20, 2014

Organizers:

This special session is organized by the co-chairs of IEEE CIS ETTC Task Force on Creative Intelligence
  • Chuan-Kang Ting, National Chung Cheng University, Taiwan. ckting@cs.ccu.edu.tw
  • Francisco Fernández de Vega, University of Extremadura, Spain. fcofdez@unex.es
  • Palle Dahlstedt, University of Gothenburg, Sweden. palle.dahlstedt@ait.gu.se

Monday 13 January 2014

Call for papers: Special session for WCCI 2014 "Intelligent Network Systems"

Aim and Scope

The impact of optimization in network environments, such as communication networks and transportation networks, on the modern economy and society has been growing steadily over the last few decades. The worldwide division of labor, the connection of distributed centers, and the increased mobility of individuals and devices lead to an increased demand for efficient solutions to solve optimization problems in network systems. With the advent of computer systems, computational intelligence approaches have been developed for systematic design, optimization, and improvement of different network systems.

The aim of the special session is to promote research and reflect the most recent advances of computational intelligence, including evolutionary computation, neural network, fuzzy systems, metaheuristic techniques and other intelligent methods, in the solution of problems in network systems. Topics of interest include, but are not limited to:
  • Communication network systems:  telecommunications; mobile, satellite, optical, and voice communications; personal communication systems; switching and routing; transmission systems; communication systems simulation; station and antenna design; information and speech processing; intrusion detection; error control coding; compression and cryptography; propagation and channel modeling, protocol design, etc.
  • Transportation and logistics network systems: transportation and supply networks; logistics; supply chain management; freight and passenger services; tracking and tracing; fleet and order management; modeling and traffic management; traffic simulation; individual and public transportation; inventory optimization; routing and scheduling, etc.
  • Social network systems: action policies; networking strategies; network and friendship management; identification of interests; advertisement of interests; hierarchical networks; distributed games; behavior analysis; inter-personal communication; group communication, etc.
  • Financial and economic network systems: system modeling; modeling payment system, market modeling; forecasting market prices; price tracking; invest strategies; portfolio strategies; measuring systemic importance of the financial system though the network topology, etc.
  • General network problems: parallel and distributed systems; networks and graph problems; unconstrained and constrained network design problems; structural and computational complexity; adaptability to environmental variations; robustness to network changes and failures; effectiveness and scalability of performance; location and link design; reliability and failure; corporate network design; location placement; network

Deadline

The deadline for submissions to this special session is 20 January 2014.

Information for Authors

1. Information on the format and templates for papers can be found here:   
    http://www.ieee-wcci2014.org/Paper%20Submission.htm
2. Papers should be submitted via the IEEE CEC 2014 paper submission site:   
    http://ieee-cis.org/conferences/cec2014/upload.php
3. Select the Special Session name in the Main Research topic dropdown list:   
    [SS10. EC10: Intelligent Network Systems]
4. Fill out the input fields, upload the PDF file of your paper and finalize your submission by the deadline of
    January 20, 2014

Organizers:

This special session is organized by IEEE CIS ISATC Task Force on Intelligent Network Systems
(TF-INS)
  • Chuan-Kang Ting, National Chung Cheng University, Taiwan. ckting@cs.ccu.edu.tw
  • Hui Cheng, Liverpool John Moores University, UK. hui.cheng@beds.ac.uk
  • Shengxiang Yang, De Montfort University, UK. syang@dmu.ac.uk
  • Jun Zhang, Sun Yat-Sen University, China. issai@mail.sysu.edu.cn
  • Zhun Fan, Shantou University, China. zfan@stu.edu.cn

Wednesday 1 January 2014

IEEE Transactions on Neural Networks and Learning Systems: Volume 25, Issue 1, January 2014

1. Guest Editorial: Learning in Nonstationary and Evolving Environments
Author(s): Robi Polikar; Cesare Alippi
Pages: 9 - 11

2. COMPOSE: A Semisupervised Learning Framework for Initially Labeled Nonstationary Streaming Data
Author(s): Karl B. Dyer; Robert Capo; Robi Polikar
Pages: 12 - 26

3. Active Learning With Drifting Streaming Data
Author(s): Indre Zliobaite; Albert Bifet; Bernhard Pfahringer; Geoffrey Holmes
Pages: 27 - 39

4. Online Bayesian Learning With Natural Sequential Prior Distribution
Author(s): Yohei Nakada; Makio Wakahara; Takashi Matsumoto
Pages: 40 - 54

5. PANFIS: A Novel Incremental Learning Machine
Author(s): Mahardhika Pratama; Sreenatha. G. Anavatti; Plamen. P. Angelov; Edwin Lughofer
Pages: 55 - 68

6. PCA Feature Extraction for Change Detection in Multidimensional Unlabeled Data
Author(s): Ludmila I. Kuncheva; William J. Faithfull
Pages: 69 - 80

7. Reacting to Different Types of Concept Drift: The Accuracy Updated Ensemble Algorithm
Author(s): Dariusz Brzezinski; Jerzy Stefanowski
Pages: 81 - 94

8. Mining Recurring Concepts in a Dynamic Feature Space
Author(s): Joao Bartolo Gomes; Mohamed Medhat Gaber; Pedro A. C. Sousa; Ernestina Menasalvas
Pages: 95 - 110

9. Dynamic Learning From Adaptive Neural Network Control of a Class of Nonaffine Nonlinear Systems
Author(s): Shi-Lu Dai; Cong Wang; Min Wang
Pages: 111 - 123

10. Learning in the Model Space for Cognitive Fault Diagnosis
Author(s): Huanhuan Chen; Peter Tino; Ali Rodan; Xin Yao
Pages: 124 - 136

11. Adaptive Approximation for Multiple Sensor Fault Detection and Isolation of Nonlinear Uncertain Systems
Author(s): Vasso Reppa; Marios M. Polycarpou; Christos G. Panayiotou
Pages: 137 - 153

12. Dealing With Concept Drifts in Process Mining
Author(s): R. P. Jagadeesh Chandra Bose; Wil M. P. van der Aalst; Indre Zliobaite; Mykola Pechenizkiy
Pages: 154 - 171

13. Adaptive Convex Combination Approach for the Identification of Improper Quaternion Processes
Author(s): Bukhari Che Ujang; Cyrus Jahanchahi; Clive Cheong Took; Danilo P. Mandic
Pages: 172 - 182

14. Developmental Perception of the Self and Action
Author(s): Ryo Saegusa; Giorgio Metta; Giulio Sandini; Lorenzo Natale
Pages: 183 - 202

15. Linguistic Decision Making for Robot Route Learning
Author(s): Hongmei He; Thomas Martin McGinnity; Sonya Coleman; Bryan Gardiner
Pages: 203 - 215

16. An Interval Type-2 Neural Fuzzy Chip With On-Chip Incremental Learning Ability for Time-Varying Data Sequence Prediction and System Control
Author(s): Chia-Feng Juang; Chi-You Chen
Pages: 216 - 228

17. Learning Geotemporal Nonstationary Failure and Recovery of Power Distribution
Author(s): Yun Wei; Chuanyi Ji; Floyd Galvan; Stephen Couvillon; George Orellana; James Momoh
Pages: 229 - 240

18. Continuous Dynamical Combination of Short and Long-Term Forecasts for Nonstationary Time Series
Author(s): Domingos Savio Pereira Salazar; Paulo Jorge Leitao Adeodato; Adrian Lucena Arnaud
Pages: 241 - 246